scholarly journals Influence of behavioral factors on decision making by individuals and nudge concept: theoretical and experimental analysis

Author(s):  
E.A. Smorodina ◽  
E.Yu. Polyakova ◽  
T.S. Kadochnikova
2016 ◽  
Vol 1 (1) ◽  
pp. 51-59
Author(s):  
Jhansi Rani Boda ◽  
G. Sunitha ◽  
Parag Ray

Objective - Investment is the commitment of funds which have been saved from the current consumption with an expectation of favorable future returns. Investment behavior is concerned with choices made about the purchase of a significant number of securities for an individual or institutional account. Individual investment behavior is relatively a new area of research in behavioral finance. This study aims to identify the various behavioral patterns of retail investors and their investment decision making in the newly formed Telangana state of India. Methodology/Technique - Data were collected from a sample of 200 retail investors via a structured questionnaire. Factor analysis was then conducted to critically identify the behavioral patterns of the retail investors. Findings - The findings of this study indicate that the two behavioral factors of Heuristics and Prospect have significant impact on the investment decision making attitudes of the retail investors. Novelty - As a newly formed state in India, the Telangana state provides potential investment opportunities for retail as well as institutional investors. It is thus, highly imperative to explore how retail investors make investment decisions especially in the newly formed Telangana State in India Type of Paper: Empirical Keywords: Behavioral Factors; Behavioral Finance; Investment Behavior; Investment Decision Making; Retail Investor.


2021 ◽  
Vol 8 (523) ◽  
pp. 13-18
Author(s):  
T. M. Panevnyk ◽  
◽  
N. K. Bolgarova ◽  

The article discusses the essence and significance of behavioral economics. The need to take into account the instrumentarium of behavioral economy in the process of solving socio-economic problems is substantiated. The macroeconomic indicators of development of Ukrainian economy are analyzed. Ukraine’s place in the world ranking in terms of GDP per capita is considered. The integrated assessment of the overall economic activity of the country using the Global Competitiveness Index (IGC), the Human Development Index (HDI), and the index of Quality of Life Index by Country are carried out. International comparison of economic growth indicators is highlighted. The dynamics of total income, expenses, savings of the population are analyzed and the significant influence of behavioral factors on decision-making in this sphere is identified, their relationship at both micro and macro levels is disclosed. A significant influence of behavioral factors on decision-making on consumption, expenses and savings is identified, their importance in crisis situations is emphasized. It is proved that the behavioral aspect of economic growth involves not just the inclusion of psychological factors in the classical analytical models, but a combination of microeconomic components with macroeconomic ones. The need to expand the analysis of economic development based on taking into account the behavioral aspect as the driving force of economic development is substantiated. It is noted that the instruments of behavioral economics should be used in the process of developing and conducting socio-economic policy. It is defined that the behavioral economy is one of the instruments that strengthens the possibilities of effective decision-making by the actors together with their impact on socio-economic processes.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ilaria Galavotti ◽  
Andrea Lippi ◽  
Daniele Cerrato

PurposeThis paper aims to develop a conceptual framework on how the representativeness heuristic operates in the decision-making process. Specifically, the authors unbundle representativeness into its building blocks: search rule, stopping rule and decision rule. Furthermore, the focus is placed on how individual-level cognitive and behavioral factors, namely experience, intuition and overconfidence, affect the functioning of this heuristic.Design/methodology/approachFrom a theoretical standpoint, the authors build on dual-process theories and on the adaptive toolbox view from the “fast and frugal heuristics” perspective to develop an integrative conceptual framework that uncovers the mechanisms underlying the representativeness heuristic.FindingsThe authors’ conceptualization suggests that the search rule used in representativeness is based on analogical mapping from previous experience, the stopping rule is the representational stability of the analogs and the decision rule is the choice of the alternative upon which there is a convergence of representations and that exceeds the decision maker's aspiration level. In this framework, intuition may help the decision maker to cross-map potentially competing analogies, while overconfidence affects the search time and costs and alters both the stopping and the decision rule.Originality/valueThe authors develop a conceptual framework on representativeness, as one of the most common, though still poorly investigated, heuristics. The model offers a nuanced perspective that explores the cognitive and behavioral mechanisms that shape the use of representativeness in decision-making. The authors also discuss the theoretical implications of their model and outline future research avenues that may further contribute to enriching their understanding of decision-making processes.


2019 ◽  
Vol 11 (8) ◽  
pp. 80
Author(s):  
Sarika Keswani ◽  
Vippa Dhingra ◽  
Bharti Wadhwa

Market anomalies and irrational behavior caused investors changes in the stock market, and this has led to an investigation into the impact of various behavioral biases and factors affecting decision-making for individual investors. The purpose of this study was to find out the effect of the four factors, heuristic, prospect, market, herding on decisions of investors at NSE. Data are collected from the questionnaire on the basis of a likert scale. To determine the reliability of the questionnaire, the Cronbach alpha factor, which was 0.728, was used. EFA and multiple regression tests have been applied. Cronbach-alpha was used to check the interal consistency of the element. Cronbach alpha emphasized to each factor: Heuristic, Prospect, Market, Herding, Investment performance and Investors decisions that consistency at an acceptable level. The result of the analysis is that the four variables have greatly influenced the investment decision and return on investment. All behavioral variables have a significant impact on the decision-making process of investors, which led to the acceptance of all assumptions regarding the level of influence of behavioral factors in decision making for individual investors.


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